Data driven employee performance and customer satisfaction

For nigh over a decade now it has been received wisdom that any organization with a direct touch point to customers is going to need a dynamic and ongoing stream of metrics that provide feedback on the efficacy or not of their customer service platform. Partly driving that thinking is the fact that up to 40% of the volume of customer service calls may not materialize if a pro-active data driven customer service response mechanism is in place; one that would have gone towards anticipating customer preferences and needs.

But an undue reliance on data and developing metrics around that may be stamping out initiatives and not rewarding intangibles. That at least is the viewpoint of a recent article in the Harvard Business Review Blog which suggests that better data may not necessarily mean better employee performance and organizational outcomes.  It cites the example of the reward system at work in schools where performance evaluations pivot around scores only to find that "higher test scores don’t necessarily translate to greater student mastery of the material. In other words, teaching methods that are effective in improving test scores may not be the best for increasing students’ knowledge."

Applying the foregoing in the work sphere the HBR blog notes that work in many organizations "leads to easily measured outcomes as in sales volume".   Complex issues like handling customer charge backs in the hotel industry, for example,  are are harder to quantify but likely lead to better customer engagement. On top of that "the rise of eHRM—electronic human-resource management has made it becomes easier than ever for organizations to automate the collection and analysis of employee data."  While this enables easy quantification it overlooks the goodwill engendered by the time-consuming but rewarding outcomes from complex transactions that result in an employee winning over an agitated customer.

The article points out that an oversimplification or over-objectifying of the measurement of performance risks missing the richness of what makes that job special—or complex—or what makes each person’s contribution unique. For many managers that "duality is not apparent" and  "managerial knowledge and skill in applying metrics has not kept up with organizations’ ability to create them".

The solution to the seeming fork in the road according to HBR is "better data" and cites the example of sabermetrics in baseball which looks for "objective knowledge" in baseball statistics.   What remains true is that a primary way at getting at the underlying causes of customer dissatisfaction is a rigorous analysis of data particularly from customer response centers whether they are call or internet based.


Published by

Vijay Dandapani

Co-founder and president of a New York based hotel company for 24 years. Grew the firm to five hotels in Manhattan and also developed a greenfield project at MacArthur airport, New York. Speaker at numerous prestigious forums including Economy Hotels World Asia, Lodging Conference, NYU, Columbia University Real Estate Roundtable, Baruch College's Zicklin School and ALIS. President and ceo of New York City Hotel Association since January 2017.